CN108873699A - A kind of chemical industry time-varying industrial process mixing control method - Google Patents
A kind of chemical industry time-varying industrial process mixing control method Download PDFInfo
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- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
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Abstract
The invention discloses a kind of chemical industry time-varying batch process mixing control methods, include the following steps：Step 1 establishes batch process time-varying state spatial model；Step 2, the batch process controller for designing controlled device.This method initially sets up batch process model, by introducing state error and output error, it is equivalent stochastic system model by above-mentioned model conversation, the probability occurred according to different faults converts more flexible more new law for conventional iterative learning design of control law and designs.Different from traditional control strategy, hybrid control strategy proposed by the invention considers actuator and the probability of different faults occurs, and system is comprehensively analyzed, handles all kinds of failures, and the flexibility of troubleshooting, rapidity are more preferable.
Description
Technical field
The invention belongs to automatic industrial process control fields, are related to a kind of chemical industry time-varying batch process mixing controlling party
Method.
Background technique
In industrial processes, batch processed process is very universal, meanwhile, it is long under complicated industrial production environment
The case where production equipment of time operation breaks down is very universal, and existing failure not only will affect production efficiency and product matter
Amount, also will cause property loss and casualties.Comprehensively consider safety in production and economic benefit, when system breaks down, is
System is still to keep certain stability and controllability.Therefore, it is necessary to study fault handling method.
Summary of the invention
The invention aims to better solve the failure that actuator occurs in chemical industry batch process, a kind ofization is proposed
Working hour becomes batch process mixing control method.This method initially sets up batch process model, by introducing state error and output
Above-mentioned model conversation is equivalent stochastic system model, the probability occurred according to different faults, by conventional iteration by error
It practises design of control law and is converted into more flexible more new law design.Different from traditional control strategy, mixing proposed by the invention
Control strategy considers actuator and the probability of different faults occurs, and system is comprehensively analyzed, handles all kinds of failures, troubleshooting
Flexibility, rapidity it is more preferable.
The technical scheme is that being devised by means such as model foundation, controller design, prediction mechanism, optimizations
A kind of chemical industry time-varying batch process mixing control method, the safety and reliability of system can be improved using this method.It has
Body technique scheme is as follows：
The step of the method for the present invention includes：
Step 1 establishes batch process time-varying state spatial model, and specific method is：
1-1. establishes a batch process system model, and form is as follows：
Wherein k and t respectively indicates batch and the batch time of running, and x (t+1, k), x (t, k), x (t-d (t), k) are k respectively
Batch t+1 moment, t moment, the system mode at t-d (t) moment, d (t) are the state delay of system t moment, dm≤d(t)≤dM,
dm、dMIt is the lower and upper limit of state delay, y (t, k) ∈ R respectivelylIt is the system output of k batch t moment, dimension Rl, u (t,
k)∈RmIt is the system input of k batch t moment, dimension Rm, l, m are the order of system output and input respectively, and σ (t, k) is indicated
Switching signal related with batch and moment, Aσ(t,k),Adσ(t,k),Bσ(t,k),Cσ(t,k)It is appropriate with switching signal to respectively indicate
The constant matrices of dimension, ωσ(t,k)(t, k) is the external disturbance of k batch t moment, and x (0, k) is the original state of k batch system,
Its initial value is set as x0,k。
The desired trajectory that 1-2. makes batch process output tracking given, is defined as follows：
e(t,k)A yr(t)-y(t,k)
Wherein yrIt (t) is t moment system output desired trajectory, e (t, k) is the system output errors of k batch t moment, A table
Show ' being defined as '.
The probability of happening of the 1-3. batch process system failure is defined as follows：
0≤P γ (t+1, k)=1 | and γ (t, k)=0 }=α≤1,0≤P γ (t+1, k)=0 | and γ (t, k)=0 }=1-
α≤1
0≤P γ (t+1, k)=1 | γ (t, k)=1 }=1- χ≤1,0≤P γ (t+1, k)=0 | γ (t, k)=1 }=
χ≤1
Wherein γ (t, k), γ (t+1, k) respectively indicate k batch t moment, t+1 moment system failure decision function, take 0 table
Showing that system is normal, takes the 1 expression system failure, α indicates the probability that system current time operates normally but subsequent time breaks down,
χ indicates the current time system failure but subsequent time restores the probability operated normally.
1-4. determination judges the generation of every batch of failure probability matrix whether related with current time.
Firstly, definition status transfer probability matrix is
Wherein p00=1- α, p01=α, p10=χ, p11=1- χ.
In turn, the n step transmission function probability matrix P of state change between batch is obtainedn。
The random iteration study control law of 1-5. batch process system is described as follows：
Wherein Δ u (t, k) indicates the system random iteration study input more new law of k batch t moment, and u (t, 0) expression starts
The system of batch t moment inputs, and is set as 0.
In the case that 1-6. batch process system may break down, system input and system mode error difference are as follows：
U (t, k)=(1- γ (t, k)) u (t, k), δ (x (t, k))=x (t, k)-x (t, k-1)
Wherein x (t, k-1) indicates the system mode of k-1 batch t moment, the system that δ (x (t, k)) indicates k batch t moment
State error.
1-7. obtains following state error and output error expression formula according to 1-1 and 1-6.
WhereinIndicate the external disturbance expanded, e (t+1, k), e (t+1, k-1) are k batch, k-1 batch t+1 moment
System output errors, y (t+1, k),yr(t+1, k) is system output and the system desired output at k batch t+1 moment, δ respectively
(x (t+1, k)), δ (x (t-d (t), k)) are the system mode error at k batch t+1 moment, t-d (t) moment respectively, A, Ad、B
C is the constant matrices of appropriate dimension respectively.
Step 2, the batch process controller for designing controlled device, specifically：
2-1. is based on step 1, and it is as follows further to obtain revised SYSTEM ERROR MODEL：
WhereinE (t+1-d (t), k-1) is the system output errors at k-1 batch t+1-d (t) moment, z (t, k)
Indicate the system global error of k batch t moment, I is the unitary matrice of appropriate dimension.
The random iteration study more new law that 2-2. further obtains system is as follows：
Δ u (t, k)=(1- γ (t, k)) K0X(t,k)
WhereinK0For the gain matrix for meeting system requirements.
2-3. repeats step 2.1 to 2.2 and continues to solve new optimal system random iteration study more new law in subsequent time
Δ u (t, k) obtains optimum control amount, acts on control object, and circuit sequentially.
Specific embodiment
By taking injection molding process as an example：
Here it is described with the filling pressure in injection molding process, regulating measure is that the valve of control proportioning valve is opened
Degree.
Step 1 establishes injection molding process time-varying state spatial model, comprises the concrete steps that：
1-1. establishes an injection molding process system model, and form is as follows：
Wherein k and t respectively indicates batch and the batch time of running of injection molding process, x (t+1, k), x (t, k), x (t-
D (t), k) it is k batch t+1 moment, t moment, the system mode at t-d (t) moment in injection molding process respectively, d (t) is injection molding
The state delay of t moment, d in forming processm≤d(t)≤dM, dm、dMIt is under the state delay in injection molding process respectively
Limit and the upper limit, y (t, k) ∈ RlIt is the filling pressure of k batch t moment in injection molding process, dimension Rl, u (t, k) ∈ RmIt is
The valve opening of k batch t moment, dimension R in injection molding processm, l, m are the filling pressure in injection molding process respectively
With the order of valve opening, σ (t, k) indicates switching signal related with batch and moment in injection molding process, Aσ(t,k),
Adσ(t,k),Bσ(t,k),Cσ(t,k)The constant matrices of the appropriate dimension in injection molding process with switching signal is respectively indicated,
ωσ(t,k)(t, k) is the external disturbance of k batch t moment in injection molding process, and x (0, k) is that k batch is infused in injection molding process
Molding original state is moulded, initial value is set as x0,k。
1-2. allows the filling pressure of injection molding process to track given filling pressure track, is defined as follows：
e(t,k)A yr(t)-y(t,k)
Wherein yr(t) be t moment in injection molding process given filling pressure track, e (t, k) is injection molding process
The filling pressure error of middle k batch t moment, A indicate ' being defined as '.
The probability of happening of 1-3. injection molding process failure is defined as follows：
0≤P γ (t+1, k)=1 | and γ (t, k)=0 }=α≤1,0≤P γ (t+1, k)=0 | and γ (t, k)=0 }=1-
α≤1
0≤P γ (t+1, k)=1 | γ (t, k)=1 }=1- χ≤1,0≤P γ (t+1, k)=0 | γ (t, k)=1 }=
χ≤1
Wherein γ (t, k), γ (t+1, k) respectively indicate k batch t moment in injection molding process, t+1 moment injection molding
System failure decision function, take 0 expression injection molding process normal operation, take 1 expression injection molding process operation troubles, α
Indicate that the probability that injection molding process current time operates normally but subsequent time breaks down, χ indicate that injection molding process is worked as
Preceding moment failure but subsequent time restore the probability of normal operation.
1-4. determination judges the generation of every batch of failure in injection molding process probability square whether related with current time
Battle array.
Firstly, the state transfer probability matrix for defining injection molding process is
Wherein p00=1- α, p01=α, p10=χ, p11=1- χ.
In turn, the n step transmission function probability matrix P of state change between injection molding process batch is obtainedn。
The random iteration study control law of 1-5. injection molding process is described as follows：
Wherein Δ u (t, k) indicates that the injection molding random iteration study valve of k batch t moment in injection molding process is opened
The more new law of degree, u (t, 0) indicate the valve opening for starting batch t moment in injection molding process.
In the case that 1-6.. injection molding process may break down, the valve opening of injection molding and injection molding
State error difference is as follows：
U (t, k)=(1- γ (t, k)) u (t, k), δ (x (t, k))=x (t, k)-x (t, k-1)
Wherein x (t, k-1) indicates the system mode of k-1 batch t moment in injection molding process, and δ (x (t, k)) indicates note
It is moulded into the system mode error of k batch t moment during type.
1-7. obtains the state error and filling pressure error expression of following injection molding process according to 1-1 and 1-6.
WhereinIndicate the external disturbance expanded in injection molding process, e (t+1, k), e (t+1, k-1) are to be molded into
K batch, the filling pressure error at k-1 batch t+1 moment, y (t+1, k), y during typer(t+1, k) is injection molding respectively
The filling pressure He desired filling pressure at k batch t+1 moment in journey, δ (x (t+1, k)), δ (x (t-d (t), k)) are injection molding respectively
The system mode error at k batch t+1 moment, t-d (t) moment in forming process, A, Ad, B C be in injection molding process respectively
Appropriate dimension constant matrices.
Step 2, the time-varying mixture control for designing injection molding process, specifically：
2-1. is based on step 1, and the error model for further obtaining revised injection molding process is as follows：
WhereinE (t+1-d (t), k-1) is the filler at k-1 batch t+1-d (t) moment in injection molding process
Pressure error, z (t, k) indicate the system global error of k batch t moment in injection molding process, and I is the tenth of the twelve Earthly Branches square of appropriate dimension
Battle array.
The random iteration study more new law that 2-2. further obtains injection molding process is as follows：
Δ u (t, k)=(1- γ (t, k)) K0X(t,k)
WhereinK0For the gain matrix for meeting injection molding process.
2-3. repeats step 2.1 to 2.2 and continues to solve new optimal injection molding process random iteration in subsequent time
More new law Δ u (t, k) is practised, optimal valve opening is obtained, acts on injection molding process, and circuit sequentially.
Claims (3)
1. a kind of chemical industry time-varying batch process mixing control method, includes the following steps：
Step 1 establishes batch process time-varying state spatial model；
Step 2, the batch process controller for designing controlled device.
2. chemical industry time-varying batch process mixing control method as described in claim 1, it is characterised in that：
Step 1 is specific as follows：
1-1. establishes a batch process system model, and form is as follows：
Wherein k and t respectively indicates batch and the batch time of running, and x (t+1, k), x (t, k), x (t-d (t), k) are k batch respectively
T+1 moment, t moment, the system mode at t-d (t) moment, d (t) are the state delay of system t moment, dm≤d(t)≤dM, dm、
dMIt is the lower and upper limit of state delay, y (t, k) ∈ R respectivelylIt is the system output of k batch t moment, dimension Rl, u (t, k)
∈RmIt is the system input of k batch t moment, dimension Rm, l, m be respectively system output and input order, σ (t, k) indicate with
Batch and moment related switching signal, Aσ(t,k),Adσ(t,k),Bσ(t,k),Cσ(t,k)Respectively indicate the appropriate dimension with switching signal
The constant matrices of degree, ωσ(t,k)(t, k) is the external disturbance of k batch t moment, and x (0, k) is the original state of k batch system,
Initial value is set as x0,k；
The desired trajectory that 1-2. makes batch process output tracking given, is defined as follows：
e(t,k)A yr(t)-y(t,k)
Wherein yrIt (t) is t moment system output desired trajectory, e (t, k) is the system output errors of k batch t moment, and A indicates ' fixed
Justice is '；
The probability of happening of the 1-3. batch process system failure is defined as follows：
0≤P γ (t+1, k)=1 | and γ (t, k)=0 }=α≤1,0≤P γ (t+1, k)=0 | and γ (t, k)=0 }=α≤1 1-
0≤P γ (t+1, k)=1 | γ (t, k)=1 }=1- χ≤1,0≤P γ (t+1, k)=0 | and γ (t, k)=1 }=χ≤1
Wherein γ (t, k), γ (t+1, k) respectively indicate k batch t moment, t+1 moment system failure decision function, take 0 expression system
System is normal, takes the 1 expression system failure, and α indicates the probability that system current time operates normally but subsequent time breaks down, χ table
Show the current time system failure but subsequent time restores the probability operated normally；
1-4. determination judges the generation of every batch of failure probability matrix whether related with current time：
Firstly, definition status transfer probability matrix is
Wherein p00=1- α, p01=α, p10=χ, p11=1- χ.
In turn, the n step transmission function probability matrix P of state change between batch is obtainedn；
The random iteration study control law of 1-5. batch process system is described as follows：
Wherein Δ u (t, k) indicates the system random iteration study input more new law of k batch t moment, and u (t, 0) indicates to start batch
The system of t moment inputs, and is set as 0；
In the case that 1-6. batch process system may break down, system input and system mode error difference are as follows：
U (t, k)=(1- γ (t, k)) u (t, k), δ (x (t, k))=x (t, k)-x (t, k-1)
Wherein x (t, k-1) indicates the system mode of k-1 batch t moment, and δ (x (t, k)) indicates the system mode of k batch t moment
Error；
1-7. obtains following state error and output error expression formula according to 1-1 and 1-6：
WhereinIndicate the external disturbance expanded, e (t+1, k), e (t+1, k-1) are k batch, k-1 batch t+1 moment to be
System output error, y (t+1, k), yr(t+1, k) is system output and the system desired output at k batch t+1 moment, δ (x (t respectively
+ 1, k)), δ (x (t-d (t), k)) be respectively k batch t+1 moment, t-d (t) moment system mode error,B C difference
It is the constant matrices of appropriate dimension.
3. chemical industry time-varying batch process mixing control method as claimed in claim 2, it is characterised in that：
Step 2 is specific as follows：
2-1. is based on step 1, and it is as follows further to obtain revised SYSTEM ERROR MODEL：
WhereinE (t+1-d (t), k-1) is the system output errors at k-1 batch t+1-d (t) moment, and z (t, k) is indicated
The system global error of k batch t moment, I are the unitary matrice of appropriate dimension；
The random iteration study more new law that 2-2. further obtains system is as follows：
Δ u (t, k)=(1- γ (t, k)) K0X(t,k)
WhereinK0For the gain matrix for meeting system requirements.；
2-3. repeats step 2.1 to 2.2 and continues to solve new optimal system random iteration study more new law Δ u in subsequent time
(t, k) obtains optimum control amount, acts on control object, and circuit sequentially.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111123871A (en) * | 2019-12-25 | 2020-05-08 | 海南师范大学 | Prediction function control method aiming at chemical process genetic algorithm optimization |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013069094A (en) * | 2011-09-22 | 2013-04-18 | Azbil Corp | Control method and controller |
| CN106896800A (en) * | 2015-12-18 | 2017-06-27 | 费希尔-罗斯蒙特系统公司 | The method and apparatus for carrying out continuous process checking using analysis/statistical modeling |
| CN107544255A (en) * | 2017-10-12 | 2018-01-05 | 杭州电子科技大学 | A kind of state compensation model control method of batch process |
| CN107831662A (en) * | 2017-11-13 | 2018-03-23 | 辽宁石油化工大学 | For the random 2D controller design methods of the batch process of actuator failures be present |
| CN107991875A (en) * | 2017-12-13 | 2018-05-04 | 杭州电子科技大学 | A kind of control method of the Chemical Batch Process enhancing model based on fail-safe analysis |
-
2018
- 2018-07-11 CN CN201810760549.9A patent/CN108873699B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2013069094A (en) * | 2011-09-22 | 2013-04-18 | Azbil Corp | Control method and controller |
| CN106896800A (en) * | 2015-12-18 | 2017-06-27 | 费希尔-罗斯蒙特系统公司 | The method and apparatus for carrying out continuous process checking using analysis/statistical modeling |
| CN107544255A (en) * | 2017-10-12 | 2018-01-05 | 杭州电子科技大学 | A kind of state compensation model control method of batch process |
| CN107831662A (en) * | 2017-11-13 | 2018-03-23 | 辽宁石油化工大学 | For the random 2D controller design methods of the batch process of actuator failures be present |
| CN107991875A (en) * | 2017-12-13 | 2018-05-04 | 杭州电子科技大学 | A kind of control method of the Chemical Batch Process enhancing model based on fail-safe analysis |
Non-Patent Citations (4)
| Title |
|---|
| LIMIN WANG ET AL.: "Average dwell time-based optimal iterative learning control for multi-phase batch processes", 《JOURNAL OF PROCESS CONTROL》 * |
| LIMIN WANG ET AL.: "Robust delay dependent iterative learning fault-tolerant control for batch processes with state delay and actuator failures", 《JOURNAL OF PROCESS CONTROL》 * |
| LIMIN WANG ET AL.: "Robust design of feedback integrated with iterative learning control for batch processes with uncertainties and interval time-varying delays", 《JOURNAL OF PROCESS CONTROL》 * |
| 王玉中: "工业过程的预测控制与模糊PID控制的研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111123871A (en) * | 2019-12-25 | 2020-05-08 | 海南师范大学 | Prediction function control method aiming at chemical process genetic algorithm optimization |
| CN111123871B (en) * | 2019-12-25 | 2023-06-23 | 海南师范大学 | Prediction function control method for genetic algorithm optimization of chemical process |
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